Inotuzumab ozogamicin in pediatric patients with relapsed/refractory acute lymphoblastic leukemia
Bibliographic record
Abstract
Although inotuzumab ozogamicin (InO) is recognized as an effective agent in relapsed acute lymphoblastic leukemia (ALL) in adults, data on safety and efficacy in pediatric patients are scarce. We report the use of InO in 51 children with relapsed/refractory ALL treated in the compassionate use program. In this heavily pretreated cohort, complete remission was achieved in 67% of patients with overt marrow disease. The majority (71%) of responders were negative for minimal residual disease. Responses were observed irrespective of cytogenetic subtype or number or type of prior treatment regimens. InO was well-tolerated; grade 3 hepatic transaminitis or hyperbilirubinemia were noted in 6 (12%) and grade 3/4 infections in 11 (22%) patients. No patient developed sinusoidal obstruction syndrome (SOS) during InO therapy; however, 11 of 21 (52%) patients who underwent hematopoietic stem cell transplantation (HSCT) following InO developed SOS. Downregulation of surface CD22 was detected as a possible escape mechanism in three patients who developed a subsequent relapse after InO. We conclude that InO is a well-tolerated, effective therapy for children with relapsed ALL and prospective studies are warranted. Identification of risk factors for developing post-HSCT SOS and strategies to mitigate this risk are ongoing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".